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The diagnosis of the presence of metastatic lymph nodes from abdominal computed tomography (CT) scans is an essential task performed by radiologists to guide radiation and chemotherapy treatment. State-of-the-art deep learning classifiers…

Computer Vision and Pattern Recognition · Computer Science 2019-10-24 Saskia Glaser , Gabriel Maicas , Sergei Bedrikovetski , Tarik Sammour , Gustavo Carneiro

Early and accurate diagnosis of interstitial lung diseases (ILDs) is crucial for making treatment decisions, but can be challenging even for experienced radiologists. The diagnostic procedure is based on the detection and recognition of the…

Computer Vision and Pattern Recognition · Computer Science 2018-04-02 Marios Anthimopoulos , Stergios Christodoulidis , Lukas Ebner , Thomas Geiser , Andreas Christe , Stavroula Mougiakakou

Multi-phase computed tomography (CT) scans use contrast agents to highlight different anatomical structures within the body to improve the probability of identifying and detecting anatomical structures of interest and abnormalities such as…

Image and Video Processing · Electrical Eng. & Systems 2024-04-18 Abdullah F. Al-Battal , Soan T. M. Duong , Van Ha Tang , Quang Duc Tran , Steven Q. H. Truong , Chien Phan , Truong Q. Nguyen , Cheolhong An

Lung cancer is highly lethal, emphasizing the critical need for early detection. However, identifying lung nodules poses significant challenges for radiologists, who rely heavily on their expertise for accurate diagnosis. To address this…

Image and Video Processing · Electrical Eng. & Systems 2023-10-17 Hossein Jafari , Karim Faez , Hamidreza Amindavar

Lung cancer ranks as one of the leading causes of cancer diagnosis and is the foremost cause of cancer-related mortality worldwide. The early detection of lung nodules plays a pivotal role in improving outcomes for patients, as it enables…

Computer Vision and Pattern Recognition · Computer Science 2025-10-28 Jiasen Zhang , Mingrui Yang , Weihong Guo , Brian A. Xavier , Michael Bolen , Xiaojuan Li

Accurately predicting and detecting interstitial lung disease (ILD) patterns given any computed tomography (CT) slice without any pre-processing prerequisites, such as manually delineated regions of interest (ROIs), is a clinically…

Computer Vision and Pattern Recognition · Computer Science 2017-01-23 Mingchen Gao , Ziyue Xu , Le Lu , Adam P. Harrison , Ronald M. Summers , Daniel J. Mollura

Accurate lymph node (LN) segmentation is critical in radiotherapy treatment and prognosis analysis, but is limited by the need for large annotated datasets. While deep learning-based segmentation foundation models show potential in…

Computer Vision and Pattern Recognition · Computer Science 2025-03-04 Zihao Luo , Zijun Gao , Wenjun Liao , Shichuan Zhang , Guotai Wang , Xiangde Luo

Lung cancer is the most common form of cancer found worldwide with a high mortality rate. Early detection of pulmonary nodules by screening with a low-dose computed tomography (CT) scan is crucial for its effective clinical management.…

Image and Video Processing · Electrical Eng. & Systems 2020-06-17 Rakshith Sathish , Rachana Sathish , Ramanathan Sethuraman , Debdoot Sheet

Predicting outcomes, such as survival or metastasis for individual cancer patients is a crucial component of precision oncology. Machine learning (ML) offers a promising way to exploit rich multi-modal data, including clinical information…

Machine Learning · Computer Science 2021-06-04 Michal Kazmierski , Benjamin Haibe-Kains

Detecting malignant pulmonary nodules at an early stage can allow medical interventions which may increase the survival rate of lung cancer patients. Using computer vision techniques to detect nodules can improve the sensitivity and the…

Image and Video Processing · Electrical Eng. & Systems 2020-10-30 Siqi Liu , Arnaud Arindra Adiyoso Setio , Florin C. Ghesu , Eli Gibson , Sasa Grbic , Bogdan Georgescu , Dorin Comaniciu

Lymph node metastasis (LNM) is a significant prognostic factor in patients with head and neck cancer, and the ability to predict it accurately is essential for treatment optimization. PET and CT imaging are routinely used for LNM…

Lung cancer is an extremely lethal disease primarily due to its late-stage diagnosis and significant mortality rate, making it the major cause of cancer-related demises globally. Machine Learning (ML) and Convolution Neural network (CNN)…

Image and Video Processing · Electrical Eng. & Systems 2025-01-03 Asha V , Bhavanishankar K

Metastatic presence in lymph nodes is one of the most important prognostic variables of breast cancer. The current diagnostic procedure for manually reviewing sentinel lymph nodes, however, is very time-consuming and subjective.…

Computer Vision and Pattern Recognition · Computer Science 2016-08-05 Richard Chen , Yating Jing , Hunter Jackson

Lung cancer is a primary contributor to cancer-related mortality globally, highlighting the necessity for precise early detection of pulmonary nodules through low-dose CT (LDCT) imaging. Deep learning methods have improved nodule detection…

Quantitative Methods · Quantitative Biology 2025-12-10 Fateme Mobini , Mohammad Reza Hedyehzadeh , Mahdi Yousefi

Lymph node metastasis is one of the most significant diagnostic indicators in breast cancer, which is traditionally observed under the microscope by pathologists. In recent years, computerized histology diagnosis has become one of the most…

Computer Vision and Pattern Recognition · Computer Science 2017-08-01 Huangjing Lin , Hao Chen , Qi Dou , Liansheng Wang , Jing Qin , Pheng-Ann Heng

Liver cancer has high morbidity and mortality rates in the world. Multi-phase CT is a main medical imaging modality for detecting/identifying and diagnosing liver tumors. Automatically detecting and classifying liver lesions in CT images…

Image and Video Processing · Electrical Eng. & Systems 2023-06-29 Fakai Wang , Chi-Tung Cheng , Chien-Wei Peng , Ke Yan , Min Wu , Le Lu , Chien-Hung Liao , Ling Zhang

This paper introduces a novel deep-learning method for the automatic detection and segmentation of lung nodules, aimed at advancing the accuracy of early-stage lung cancer diagnosis. The proposed approach leverages a unique "Channel Squeeze…

Image and Video Processing · Electrical Eng. & Systems 2024-09-24 Mingxiu Sui , Jiacheng Hu , Tong Zhou , Zibo Liu , Likang Wen , Junliang Du

Cancer is the uncontrollable cell division of abnormal cells inside the human body, which can spread to other body organs. It is one of the non-communicable diseases (NCDs) and NCDs accounts for 71% of total deaths worldwide whereas lung…

Image and Video Processing · Electrical Eng. & Systems 2021-12-28 Neha Baranwal , Preethi Doravari , Renu Kachhoria

Lung cancer, a malignancy originating in lung tissues, is commonly diagnosed and classified using medical imaging techniques, particularly computed tomography (CT). Despite the integration of machine learning and deep learning methods, the…

Image and Video Processing · Electrical Eng. & Systems 2025-10-21 Olajumoke O. Adekunle , Joseph D. Akinyemi , Khadijat T. Ladoja , Olufade F. W. Onifade

Lung cancer accounts for the highest number of cancer deaths globally. Early diagnosis of lung nodules is very important to reduce the mortality rate of patients by improving the diagnosis and treatment of lung cancer. This work proposes an…

Computer Vision and Pattern Recognition · Computer Science 2016-05-27 Tizita Nesibu Shewaye , Alhayat Ali Mekonnen